update app.

app.py

@@ -13,10 +13,13 @@ model_id = "dicoo_model"
 pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float)
 
 def predict(prompt, steps=30, seed=42, guidance_scale=7.5):
+    # cpu info
+    # print(subprocess.check_output(["cat /proc/cpuinfo | grep 'model name' |uniq"], stderr=subprocess.STDOUT).decode("utf8"))
     print("prompt: ", prompt)
     print("steps: ", steps)
+    generator = torch.manual_seed(seed)
     start_time = time.time()
-    image = pipe(prompt, num_inference_steps=steps, guidance_scale=7.5).images[0]
+    image = pipe(prompt, generator=generator, num_inference_steps=steps, guidance_scale=7.5).images[0]
     print("cost: ", time.time() - start_time)
     return image